Gui at MixMT 2022 : English-Hinglish: An MT approach for translation of code mixed data
Abstract
Code-mixed machine translation has become an important task in multilingual communities and extending the task of machine translation to code mixed data has become a common task for these languages. In the shared tasks of WMT 2022, we try to tackle the same for both English + Hindi to Hinglish and Hinglish to English. The first task dealt with both Roman and Devanagari script as we had monolingual data in both English and Hindi whereas the second task only had data in Roman script. To our knowledge, we achieved one of the top ROUGE-L and WER scores for the first task of Monolingual to Code-Mixed machine translation. In this paper, we discuss the use of mBART with some special pre-processing and post-processing (transliteration from Devanagari to Roman) for the first task in detail and the experiments that we performed for the second task of translating code-mixed Hinglish to monolingual English.
Cite
@article{arxiv.2210.12215,
title = {Gui at MixMT 2022 : English-Hinglish: An MT approach for translation of code mixed data},
author = {Akshat Gahoi and Jayant Duneja and Anshul Padhi and Shivam Mangale and Saransh Rajput and Tanvi Kamble and Dipti Misra Sharma and Vasudeva Varma},
journal= {arXiv preprint arXiv:2210.12215},
year = {2022}
}